Comparing a repeated measures variable and within-subject nested subgroups

[Jason2020]

This data set below is part of a larger set for an experiment to compare 2 treatments (GROUP) and the outcome variable is millimeter measurements (DEPTH) made on teeth nested within subjects. The measurements were made at 4 time points (WEEKS), and there are some missing values for DEPTH. Also, although most subjects have 2 treated teeth (one for each treatment), some subjects have more than 2 treated teeth. I would like to fit a repeated measures model to compare the 2 treatment groups, and later I may include other covariates in the model. Is the following model adequate? If not, I would appreciate it if someone would suggest applicable modifications.

Thanks you.

The data set (partial):

Subj Tooth  Group  Depth  Weeks

  1   AA      A      3   BASELINE

  1   AA      A      0     6

  1   AA      A      .     12

  1   AA      A      .     24

  1   BB      B      4   BASELINE

  1   BB      B      3     6

  1   BB      B      .     12

  1   BB      B      .     24

  2   CC      B      2    BASELINE

  2   CC      B      0     6

  2   CC      B      0     12

  2   CC      B      0     24

  2   AA      A      3    BASELINE

  2   AA      A      0     6

  2   AA      A      0     12

  2   AA      A      0     24

  2   GG      A      5    BASELINE

  2   GG      A      1     6

  2   GG      A      1     12

  2   GG      A      2     24

The proposed model:

PROC MIXED data=long;

 Class subj tooth group;

 Model depth = group | weeks;

 Repeated weeks / subject=tooth(subj) Group=group ;

Run;

[Jason2020]

I forgot to mention that subjects are a random sample, teeth are also random term within subjects, and time (WEEKS) is a fixed term.